Microelectronic imager devices are used in digital cameras, wireless devices with picture capabilities, and many other applications. Cellular telephones, personal digital assistants (PDAs), computers, and stand alone cameras, for example, are incorporating microelectronic imager devices for capturing and sending pictures. The growth rate of microelectronic imager devices has been steadily increasing as they become smaller and produce better images having higher pixel counts.
Microelectronic imager devices include image sensors that use charged coupled device (CCD) systems, complementary metal-oxide semiconductor (CMOS) systems or other imager technology. CCD image sensors have been widely used in digital cameras and other applications. CMOS image sensors are also popular because they have low production costs, high yields, and small sizes.
In an imager device, a pixel array comprises a plurality of pixels, each containing a photosensitive element, arranged in a predetermined number of columns and rows. The pixels are used to receive and store light. Each pixel in the array typically has an individual assigned address. The pixels of a pixel array generate signals representing incident light, which are then digitized and processed to produce image data.
One or more pixels in a pixel array may be defective, generating an inaccurate pixel signal. This inaccurate pixel signal can cause distortion or other undesirable effects in the image generated from the pixel signal. Defective pixels can be identified and corrected dynamically by using an image processor that identifies whether a pixel signal indicates a defective pixel by comparing the pixel signal to those output by neighboring pixels or to some threshold value, and, if so, replacing the pixel signal with a new value computed by the processor.
While this dynamic method can alleviate the undesirable effect of single defective pixels in an imager array without noticeable degradation of the image, when multiple neighboring pixels are defective, the image processor may not be able to compare all of the neighboring pixels and accurately determine whether certain pixels are defective. Multiple neighboring defective pixels are commonly known as a defective “cluster.” Algorithms exist which are designed to dynamically correct defective clusters; typically, however, image degradation is a very noticeable end result. Particularly, dynamic correction is not desirable when pixels in the cluster exhibit defects in the same color plane.
For this reason, pixel signals may also be corrected using a memory-based correction scheme. Defective pixels are identified during the-manufacturing of the imager device, and their addresses stored in programmable m emory of a correction circuit, such as, e.g., a fuse bank. Once the addresses of the defective pixels are stored, a correction scheme can be applied to the signals generated by these pixels. Examples of correction schemes may include interpolation of neighboring pixel signals, substituting the median value of neighboring pixel signals, or copying of a neighboring pixel's signal.
As pixel array designs become more complex, however, so do the effects of defective clusters. For example, defective clusters may form in groups which are difficult to correct, such as a group of four defective pixels with one pixel in each quadrant surrounding a non-defective pixel. Defective clusters are also becoming larger. Correction schemes applied to large defective clusters are more likely to cause visible distortion in an image.
With current memory-based correction schemes, all pixel signals from pixels identified as defective are corrected for every image capture, regardless of the exposure conditions of the particular image. Defective clusters, however, may be noticeable under certain exposure conditions but not noticeable under others. For example, under low-light exposure conditions, a plurality of pixels in an area may produce defective signals, forming a noticeable defective cluster; whereas under midlevel-light conditions, only a single defective pixel signal or no defective pixel signal at all may be produced. FIG. 1 shows an example of a pixel array 110 under both midlevel (e.g., 20 ms integration time) and dark (e.g., 200 ms integration time) exposure conditions. Under the midlevel exposure condition, only a single pixel 112 in the pixel array produces inaccurate output. Under the darker exposure condition, however, a defective cluster 114 is visible.
Currently, the same correction would be applied to the pixel signals in the array, regardless of the exposure conditions. When correction is not necessary, applying a correction scheme can unnecessarily cause the undesirable image degradation described above. Further, some correction schemes may be more appropriate for certain exposure conditions. Accordingly, there is a need and desire to determine whether or not to correct a pixel based upon existing operating or exposure conditions of an imager device, and to determine which correction scheme to apply.